ASSIST-IoT Multimodal Fall Detection Dataset
Creators
- 1. Warsaw University of Technology, Poland
- 2. Central Institute for Labour Protection – National Research Institute, Poland
Description
Multimodal dataset for fall detection. Includes acceleration data collected from a tag and two smartwatches, and location reported by the tag. More details about the data collection procedure can be found in notes.md
.
Contents
The repository contains:
data/location_data.csv
anddata/full_acceleration
– preprocessed acceleration and location data from 10 participants and mannequin simulated falls with target variable identifieddata/subsampled_acceleration_data.csv
– subsampled acceleration dataset used for training the AI modelnotes.md
– description of activities performed and notes from data collectionvideos
– reference videos for performed activities
Authors
- Piotr Sowiński – research methodology, data collection and processing
- Monika Kobus – research methodology, data collection
- Anna Dąbrowska – research methodology, methodological supervision
- Kajetan Rachwał – data collection
- Karolina Bogacka – research methodology
- Krzysztof Baszczyński – research methodology, data collection
- Anastasiya Danilenka – research methodology, data collection and processing
Acknowledgements
This work is part of the ASSIST-IoT project that has received funding from the EU’s Horizon 2020 research and innovation programme under grant agreement No 957258.
The Central Institute for Labour Protection – National Research Institute provided facilities and equipment for data collection.
License
The dataset is licensed under the Creative Commons Attribution 4.0 International License.
Files
ASSIST-IoT-SRIPAS/multimodal-fall-detection-dataset-v1.0.0.zip
Files
(166.1 MB)
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Additional details
Related works
- Is supplement to
- https://github.com/ASSIST-IoT-SRIPAS/multimodal-fall-detection-dataset/tree/v1.0.0 (URL)